“The architecture of the state was transformed in favour of the interests of companies”: corporate political activity of the food industry in Colombia
Bibliographic record
Abstract
BACKGROUND: In Colombia, public health policies to improve food environments, including front-of-pack nutrition labelling and marketing restrictions for unhealthy products, are currently under development. Opposition to these policies by the food industry is currently delaying and weakening these efforts. This opposition is commonly known as 'corporate political activity' (CPA) and includes instrumental (action-based) strategies and discursive (argument-based) strategies. Our aim was to identify the CPA of the food industry in Colombia. METHODS: We conducted a document analysis of information available in the public domain published between January-July 2019. We triangulated this data with interviews with 17 key informants. We used a deductive approach to data analysis, based on an existing framework for the CPA of the food industry. RESULTS: We identified 275 occurrences of CPA through our analysis of publicly available information. There were 197 examples of instrumental strategies and 138 examples of discursive strategies (these categories are not mutually exclusive, 60 examples belong to both categories). Interview participants also shared information about the CPA in the country. The industry used its discursive strategies to portray the industry in a 'better light', demonstrating its efforts in improving food environments and its role in the economic development of the country. The food industry was involved in several community programmes, including through public private initiatives. The industry also captured the media and tried to influence the science on nutrition and non-communicable diseases. Food industry actors were highly prominent in the policy sphere, through their lobbying, close relationships with high ranking officials and their support for self-regulation in the country. CONCLUSIONS: The proximity between the industry, government and the media is particularly evident and remains largely unquestioned in Colombia. The influence of vulnerable populations in communities and feeling of insecurity by public health advocates is also worrisome. In Colombia, the CPA of the food industry has the potential to weaken and delay efforts to develop and implement public health policies that could improve the healthiness of food environments. It is urgent that mechanisms to prevent and manage the influence of the food industry are developed in the country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".